An expanded model for perceptual visual single object recognition system using expectation priming following neuroscientific evidence

Under numerous circumstances, humans recognize visual objects in their environment with remarkable response times and accuracy. Existing artificial visual object recognition systems have not yet surpassed human vision, especially in its universality of application. We argue that modeling the recognition process in an exclusive feedforward manner hinders those systems’ performance. To bridge that performance gap between them and human vision, we present a brief review of neuroscientific data, which suggests that considering an agent’s internal influences (from cognitive systems that peripherally interact with visual-perceptual processes) recognition can be improved. Then, we propose a model for visual object recognition which uses these systems’ information, such as affection, for generating expectation to prime the object recognition system, thus reducing its execution times. Later, an implementation of the model is described. Finally, we present and discuss an experiment and its results.     

Attention to distinguishing features in object recognition

This study advances the hypothesis that, in the course of object recognition, attention is directed to distinguishing features: visual information that is diagnostic of object identity in a specific context. In five experiments, observers performed an object categorization task involving drawings of fish (Experiments 1–4) and photographs of natural sea animals (Experiment 5). Allocation of attention to distinguishing and non-distinguishing features was examined using primed-matching (Experiment 1) and visual probe (Experiments 2, 4, 5) methods, and manipulated by spatial precuing (Experiment 3). Converging results indicated that in performing the object categorization task, attention was allocated to the distinguishing features in a context-dependent manner, and that such allocation facilitated performance. Based on the view that object recognition, like categorization, is essentially a process of discrimination between probable alternatives, the implications of the findings for the role of attention to distinguishing features in object recognition are discussed.     

Orientation-invariant object recognition: evidence from repetition blindness

The question of whether object recognition is orientation-invariant or orientation-dependent was investigated using a repetition blindness (RB) paradigm. In RB, the second occurrence of a repeated stimulus is less likely to be reported, compared to the occurrence of a different stimulus, if it occurs within a short time of the first presentation. This failure is usually interpreted as a difficulty in assigning two separate episodic tokens to the same visual type. Thus, RB can provide useful information about which representations are treated as the same by the visual system. Two experiments tested whether RB occurs for repeated objects that were either in identical orientations, or differed by 30, 60, 90, or 180 degrees . Significant RB was found for all orientation differences, consistent with the existence of orientation-invariant object representations. However, under some circumstances, RB was reduced or even eliminated when the repeated object was rotated by 180 degrees , suggesting easier individuation of the repeated objects in this case. A third experiment confirmed that the upside-down orientation is processed more easily than other rotated orientations. The results indicate that, although object identity can be determined independently of orientation, orientation plays an important role in establishing distinct episodic representations of a repeated object, thus enabling one to report them as separate events.     

Novel object detection and recognition system based on points of interest selection and SVM classification

Due to the progression in computer vision technology, object recognition systems have gained considerable research interest. Though there are numerous object recognition systems in the literature, there is always a constant demand for better object recognition systems. Taking this as a challenge, this work proposes a novel object recognition system based on points of interest and feature extraction. Initially, the points of interest of the image are selected by means of Derivative Kadir-Brady (DKB) detector and the neighbourhood pixels of a particular window size are selected for further processing. The gabor and curvelet features are extracted from the area of interest, followed by the Support Vector Machine (SVM) classification. The performance of the proposed object recognition system is evaluated against three analogous techniques in terms of accuracy, precision, recall and F-measure. On experimental analysis, it is proven that the proposed approach outperforms the existing approaches and the performance of the proposed work is satisfactory.     

Conceptual knowledge attenuates viewpoint dependency in visual object recognition

Learning verbal semantic knowledge for objects has been shown to attenuate recognition costs incurred by changes in view from a learned viewpoint. Such findings were attributed to the semantic or meaningful nature of the learned verbal associations. However, recent findings demonstrate surprising benefits to visual perception after learning even noninformative verbal labels for stimuli. Here we test whether learning verbal information for novel objects, independent of its semantic nature, can facilitate a reduction in viewpoint-dependent recognition. To dissociate more general effects of verbal associations from those stemming from the semantic nature of the associations, participants learned to associate semantically meaningful (adjectives) or nonmeaningful (number codes) verbal information with novel objects. Consistent with a role of semantic representations in attenuating the viewpoint-dependent nature of object recognition, the costs incurred by a change in viewpoint were attenuated for stimuli with learned semantic associations relative to those associated with nonmeaningful verbal information. This finding is discussed in terms of its implications for understanding basic mechanisms of object perception as well as the classic viewpoint-dependent nature of object recognition.     

Dissociating the effects of angular disparity and image similarity in mental rotation and object recognition

Performance is often impaired linearly with increasing angular disparity between two objects in tasks that measure mental rotation or object recognition. But increased angular disparity is often accompanied by changes in the similarity between views of an object, confounding the impact of the two factors in these tasks. We examined separately the effects of angular disparity and image similarity on handedness (to test mental rotation) and identity (to test object recognition) judgments with 3-D novel objects. When similarity was approximately equated, an effect of angular disparity was only found for handedness but not identity judgments. With a fixed angular disparity, performance was better for similar than dissimilar image pairs in both tasks, with a larger effect for identity than handedness judgments. Our results suggest that mental rotation involves mental transformation procedures that depend on angular disparity, but that object recognition is predominately dependent on the similarity of image features.     

Implicit and explicit object recognition at very large visual eccentricities: No improvement after loss of central vision

Little is known about the ability of human observers to process objects in the far periphery of their visual field and nothing about its evolution in case of central vision loss. We investigated implicit and explicit recognition at two large visual eccentricities. Pictures of objects were centred at 30° or 50° eccentricity. Implicit recognition was tested through a priming paradigm. Participants (normally sighted observers and people with 10–20 years of central vision loss) categorized pictures as animal/transport both in a study phase (Block 1) and in a test phase (Block 2). In explicit recognition participants decided for each picture presented in Block 2 whether it had been displayed in Block 1 (“yes”/“no”). Both visual (identical) and conceptual/lexical (same-name) priming occurred at 30° and at 50°. Explicit recognition was observed only at 30°. In people with central vision loss testing was only performed at 50° eccentricity. The pattern of results was similar to that of normally sighted observers but global performance was lower. The results suggest that vision, at large eccentricity, is mainly based on nonconscious coarse representations. Moreover, after 10–20 years of central vision loss, no evidence was found for an increased ability to use peripheral information in object recognition.     

The role of surface-based representations of shape in visual object recognition

This study contrasted the role of surfaces and volumetric shape primitives in three-dimensional object recognition. Observers (N?=?50) matched subsets of closed contour fragments, surfaces, or volumetric parts to whole novel objects during a whole–part matching task. Three factors were further manipulated: part viewpoint (either same or different between component parts and whole objects), surface occlusion (comparison parts contained either visible surfaces only, or a surface that was fully or partially occluded in the whole object), and target–distractor similarity. Similarity was varied in terms of systematic variation in nonaccidental (NAP) or metric (MP) properties of individual parts. Analysis of sensitivity (d′) showed a whole–part matching advantage for surface-based parts and volumes over closed contour fragments—but no benefit for volumetric parts over surfaces. We also found a performance cost in matching volumetric parts to wholes when the volumes showed surfaces that were occluded in the whole object. The same pattern was found for both same and different viewpoints, and regardless of target–distractor similarity. These findings challenge models in which recognition is mediated by volumetric part-based shape representations. Instead, we argue that the results are consistent with a surface-based model of high-level shape representation for recognition.     

The properties of object representations constructed during visual search in natural scenes

To investigate properties of object representations constructed during a visual search task, we manipulated the proportion of trials/task within a block: In a search-frequent block, 80% of trials were search tasks; remaining trials presented a memory task; in a memory-frequent block, this proportion was reversed. In the search task, participants searched for a toy car (Experiments 1 and 2) or a T-shape object (Experiment 3). In the memory task, participants had to memorize objects in a scene. Memory performance was worse in the search-frequent block than in the memory-frequent block in Experiments 1 and 3, but not in Experiment 2 (token change in Experiment 1; type change in Experiments 2 and 3). Experiment 4 demonstrated that lower performance in the search-frequent block was not due to eye-movement behaviour. Results suggest that object representations constructed during visual search are different from those constructed during memorization and they are modulated by type of target.     

Role of the secondary visual cortex in HMAX model for object recognition

The models inspired by visual systems of life creatures (e.g., human, mammals, etc.) have been very successful in addressing object recognition tasks. For example, Hierarchical Model And X (HMAX) effectively recognizes different objects by modeling the V1, V4, and IT regions of the human visual system. Although HMAX is one of the superior models in the field of object recognition, its implementation has been limited due to some disadvantages such as the unrepeatability of the process under constant conditions, extreme redundancy, high computational load, and time-consuming. In this paper, we aim at revising the HMAX approach by adding the model of the secondary region (V2) in the human visual system which leads to removing the mentioned drawbacks of standard HMAX. The added layer selects repeatable and more informative features that increase the accuracy of the proposed method by avoiding the redundancy existing in the conventional approaches. Furthermore, this feature selection strategy considerably reduces the huge computational load. Another contribution of our model is highlighted when a small number of training images is available where our model can efficiently cope with this issue. We evaluate our proposed approach using Caltech5 and GRAZ-02 database as two famous benchmarks for object recognition tasks. Additionally, the results are compared with standard HMAX that validate and highlight the efficiency of the proposed method.     

Quantifying the role of context in visual object recognition

An object's context may serve as a source of information for recognition when the object's image is degraded. The current study aimed to quantify this source of information. Stimuli were photographs of objects divided into quantized blocks. Participants decreased block size (increasing resolution) until identification. Critical resolution was compared across three conditions: (1) when the picture of the target object was shown in isolation, (2) in the object's contextual setting where that context was unfamiliar to the participant, and (3) where that context was familiar to the participant. A second experiment assessed the role of object familiarity without context. Results showed a profound effect of context: Participants identified objects in familiar contexts with minimal resolution. Unfamiliar contexts required higher-resolution images, but much less so than those without context. Experiment 2 found a much smaller effect of familiarity without context, suggesting that recognition in familiar contexts is primarily based on object-location memory.     

Negative priming of unattended part primes: Implications for models of holistic and analytic processing in object recognition

The “hybrid” model of object recognition (Hummel, 2001) proposes that unattended objects are processed holistically, while attended objects are processed both holistically and analytically. Supporting evidence for this claim was reported by Thoma, Hummel, and Davidoff (2004) who showed that, unlike whole object primes, unattended split object parts (presumed to require analytic processing) do not elicit repetition priming. Here we tested the generality of this finding by contrasting priming for whole and part prime stimuli as a function of prime informativeness and by modifying the design so that both unattended whole and part prime displays contained a single perceptual object. Unlike Thoma et al. (2004) the results showed negative (rather than an absence of) priming for unattended half object primes. These findings place new constraints on theoretical models of the role of attention in object recognition.     

Sleep deprivation impairs object recognition in mice

Many studies in animals and humans suggest that sleep facilitates learning, memory consolidation, and retrieval. Moreover, sleep deprivation (SD) incurred after learning, impaired memory in humans, mice, rats, and hamsters. We investigated the importance of sleep and its timing in an object recognition task in OF1 mice subjected to 6h SD either immediately after the acquisition phase (0-6 SD) or 6h later (7-12 SD), and in corresponding undisturbed controls. Motor activity was continuously recorded with infrared sensors. All groups explored two familiar, previously encountered objects to a similar extent, both at the end of the acquisition phase and 24h later during the test phase, indicating intact familiarity detection. During the test phase 0-6 SD mice failed to discriminate between the single novel and the two familiar objects. In contrast, the 7-12 SD group and the two control groups explored the novel object significantly longer than the two familiar objects. Plasma corticosterone levels determined after SD did not differ from time-matched undisturbed controls, but were significantly below the level measured after learning alone. ACTH did not differ between the groups. Therefore, it is unlikely that stress contributed to the memory impairment. We conclude that the loss of sleep and the activities the mice engaged in during the SD, impaired recognition memory retrieval, when they occurred immediately after acquisition. The delayed SD enabled memory consolidation during the 6h when the mice were allowed to sleep, and had no detrimental effect on memory. Neither SD schedule impaired object familiarity processing, suggesting that only specific cognitive abilities were sensitive to the intervention. Sleep may either actively promote memory formation, or alternatively, sleep may provide optimal conditions of non-interference for consolidation.     

An ERP study on self-relevant object recognition

We performed an event-related potential study to investigate the self-relevance effect in object recognition. Three stimulus categories were prepared: SELF (participant's own objects), FAMILIAR (disposable and public objects, defined as objects with less-self-relevant familiarity), and UNFAMILIAR (others' objects). The participants' task was to watch the stimuli passively. Results showed that left-lateralized N250 activity differentiated SELF and FAMILIAR from UNFAMILIAR, but SELF and FAMILIAR were not differentiated. In the later time-course, SELF was dissociated from FAMILIAR, indicating the self-relevance effect in object recognition at this stage. This activity did not show consistent lateralization, in contrast to previous studies reporting right lateralization in self-relevant face and name recognition. We concluded that in object recognition, self-relevance was processed by higher-order cognitive functions later than 300ms after stimulus onset.     

Parts and wholes in person recognition: developmental trends

This study's aim is the investigation of short-term visual person recognition in 8- and 10-year-olds and adults, within the part-whole paradigm introduced by. Natural unfamiliar whole persons were contrasted with natural unfamiliar faces to test for differences between person processing and face processing. Two experiments showed advantages of whole face recognition over isolated face feature recognition. Also, these was a complete over part probe advantage (CPA, ) for person recognition in all age groups. Thus, recognition became more accurate between 8 years and adulthood, but no developmental shift in visual information processing was observable with face and whole person recognition. I conclude that person recognition does not rely on processes completely different from those of face recognition and that this holds for 8- and 10-year-olds as well as for adults.     

Face recognition algorithms and the other‐race effect: computational mechanisms for a developmental contact hypothesis

People recognize faces of their own race more accurately than faces of other races. The “contact” hypothesis suggests that this “other‐race effect” occurs as a result of the greater experience we have with own‐ versus other‐race faces. The computational mechanisms that may underlie different versions of the contact hypothesis were explored in this study. We replicated the other‐race effect with human participants and evaluated four classes of computational face recognition algorithms for the presence of an other‐race effect. Consistent with the predictions of a developmental contact hypothesis, “experience‐based models” demonstrated an other‐race effect only when the representational system was developed through experience that warped the perceptual space in a way that was sensitive to the overall structure of the model's experience with faces of different races. When the model's representation relied on a feature set optimized to encode the information in the learned faces, experience‐based algorithms recognized minority‐race faces more accurately than majority‐race faces. The results suggest a developmental learning process that warps the perceptual space to enhance the encoding of distinctions relevant for own‐race faces. This feature space limits the quality of face representations for other‐race faces.     

Bio-inspired cognitive model of motor learning by imitation

Learning, and even more so by imitation, is an essential Cognitive Functions because it is carried out throughout life and allows us to adapt our behaviors from other beings through observation. In this work, we propose a model, and implementation of the cognitive function of imitation motor learning (IML), based on psychological and neuroscientific evidence. According to the evidence, learning by imitation includes imitation of action and imitation of action over an object sub-processes. The imitation of action consists of the movement of the limbs. The imitation of action over an object consists of the interaction with an object within the environment. We achieve an implementation of the proposed model for IML and endow a virtual entity with it. In order to validate the proposal, we use a case study to analyze the sub-processes performance. From results, we conclude that both imitation of action and imitation of action over an object sub-processes play an essential role in getting the agent to interact with stimuli within the environment.